Gelling of alginate fibres

Equipment was developed to measure the time for complete gelling of sodium alginate fibres in calcium chloride solution, taken as the time to achieve maximum tensile strength. The effects of fibre diameter, alginate concentration, alginate composition and calcium chloride concentration on gelling time were investigated. A diffusional model, developed to predict the gelling time, agreed with experimental results except for the effect of calcium ion concentration which was modelled empirically.     

The role of electrostatic interactions in the mechanism of peptide bond hydrolysis by a Ser-Lys catalytic dyad

General-base catalysis in the active site of serine proteasesis carried out by the imidazole side chain of a histidine. Duringformation of the transition state, an adjacent carboxylic acidgroup stabilizes the positive charge that forms on the general-basecatalyst and as a result contributes several orders of magnitudeto the catalytic efficiency of these enzymes. In the recentlydiscovered family of self-cleaving proteins exemplified by theLexA repressor of Escherichia coli, instead of the imidazoleof a histidine, the active-site general-base catalyst was foundto be the -amino of a lysine. The considerably higher capacityof the lysine side chain for proton acceptance raises interestingquestions concerning the role of electrostatic interactionsin the mechanism of proton transfer by this highly basic group.The negative charge elimination studies described here and theireffects on the k_max and pK of LexA self-cleavage are consistentwith a model in which electrostatic interactions between anacidic side chain and the general-base catalyst form a barrierto proton transfer. The implications are that the -amino group,unlike the imidazole group, is capable of effecting proton transferwithout the intervention of a countercharge.     

Color image segmentation using adaptive unsupervised clustering approach

This paper presents the Region Splitting and Merging-Fuzzy C-means Hybrid Algorithm (RFHA), an adaptive unsupervised clustering approach for color image segmentation, which is important in image analysis and in understanding pattern recognition and computer vision field. Histogram thresholding technique is applied in the formation of all possible cells, used to split the image into multiple homogeneous regions. The merging technique is applied to merge perceptually close homogeneous regions and obtain better initialization for the Fuzzy C-means clustering approach. Experimental results have demonstrated that the proposed scheme could obtain promising segmentation results, with 12% average improvement in clustering quality and 63% reduction in classification error compared with other existing segmentation approaches.     

Experience with model-based performance, reliability, and adaptability assessment of a complex industrial architecture

In this paper, we report on our experience with the application of validated models to assess performance, reliability, and adaptability of a complex mission critical system that is being developed to dynamically monitor and control the position of an oil-drilling platform. We present real-time modeling results that show that all tasks are schedulable. We performed stochastic analysis of the distribution of task execution time as a function of the number of system interfaces. We report on the variability of task execution times for the expected system configurations. In addition, we have executed a system library for an important task inside the performance model simulator. We report on the measured algorithm convergence as a function of the number of vessel thrusters. We have also studied the system architecture adaptability by comparing the documented system architecture and the implemented source code. We report on the adaptability findings and the recommendations we were able to provide to the system’s architect. Finally, we have developed models of hardware and software reliability. We report on hardware and software reliability results based on the evaluation of the system architecture.     

Improving the non-extensive medical image segmentation based on Tsallis entropy

Thresholding techniques for image segmentation is one of the most popular approaches in Computational Vision systems. Recently, M. Albuquerque has proposed a thresholding method (Albuquerque et al. in Pattern Recognit Lett 25:1059–1065, 2004) based on the Tsallis entropy, which is a generalization of the traditional Shannon entropy through the introduction of an entropic parameter q. However, the solution may be very dependent on the q value and the development of an automatic approach to compute a suitable value for q remains also an open problem. In this paper, we propose a generalization of the Tsallis theory in order to improve the non-extensive segmentation method. Specifically, we work out over a suitable property of Tsallis theory, named the pseudo-additive property, which states the formalism to compute the whole entropy from two probability distributions given an unique q value. Our idea is to use the original M. Albuquerque’s algorithm to compute an initial threshold and then update the q value using the ratio of the areas observed in the image histogram for the background and foreground. The proposed technique is less sensitive to the q value and overcomes the M. Albuquerque and k-means algorithms, as we will demonstrate for both ultrasound breast cancer images and synthetic data.     

Hand gesture recognition from depth and infrared Kinect data for CAVE applications interaction

This paper presents a real-time framework that combines depth data and infrared laser speckle pattern (ILSP) images, captured from a Kinect device, for static hand gesture recognition to interact with CAVE applications. At the startup of the system, background removal and hand position detection are performed using only the depth map. After that, tracking is started using the hand positions of the previous frames in order to seek for the hand centroid of the current one. The obtained point is used as a seed for a region growing algorithm to perform hand segmentation in the depth map. The result is a mask that will be used for hand segmentation in the ILSP frame sequence. Next, we apply motion restrictions for gesture spotting in order to mark each image as a ‘Gesture’ or ‘Non-Gesture’. The ILSP counterparts of the frames labeled as “Gesture” are enhanced by using mask subtraction, contrast stretching, median filter, and histogram equalization. The result is used as the input for the feature extraction using a scale invariant feature transform algorithm (SIFT), bag-of-visual-words construction and classification through a multi-class support vector machine (SVM) classifier. Finally, we build a grammar based on the hand gesture classes to convert the classification results in control commands for the CAVE application. The performed tests and comparisons show that the implemented plugin is an efficient solution. We achieve state-of-the-art recognition accuracy as well as efficient object manipulation in a virtual scene visualized in the CAVE.     

Sub-1 V band-gap based and MOS threshold-voltage based voltage references in 0.13 µm CMOS

Portable and implantable device applications require low supply voltage reference circuits due to increasing trend for lower power requirements. Voltage references have been proposed for operation below 1 V for CMOS and a comprehensive analysis of the behavior of the different topologies is needed for ultra-low power designs, in order to select the right circuit topology for a given requirement. This work compares two major classes of voltage reference topologies: threshold voltage (V_T0)-based and (V_G0) bandgap voltage-based reference circuits. Four different topologies of voltage-reference designs with 1-V supply were designed and fabricated in 130 nm CMOS process. Monte Carlo analysis shows the variability of the references and of their temperature coefficients (TC), and the results are compared to measured samples. Simulations and measurements show that the threshold voltage-based references are more susceptible to the variations in the CMOS fabrication process.     

Maternal Flaxseed Oil During Lactation Enhances Bone Development in Male Rat Pups

Flaxseed oil is an alpha linolenic acid source important in the growth and body development stage; furthermore, this acid acts on adipose tissue and bone health. The aim of this study was to evaluate body composition, fatty acid composition, hormone profile, retroperitoneal adipocyte area and femur structure of pups at weaning, whose mothers were fed a diet containing flaxseed oil during lactation. After birth, pups were randomly assigned: control (C, n = 12) and flaxseed oil (FO, n = 12), rats whose mothers were treated with diet containing soybean or flaxseed oil. At 21 days, the pups were weaned and body mass, length, body composition, biochemical parameter, leptin, osteoprotegerin, osteocalcin, fatty acids composition, intra‐abdominal fat mass and femur structure were analyzed. FO showed (p < 0.05): higher body mass (+12 %) and length (+9 %); body fat mass (g, +45 %); bone mineral density (+8 %), bone mineral content (+55 %) and bone area (+35 %), osteocalcin (+173 %) and osteoprotegerin (+183 %). Arachidonic acid was lower (p < 0.0001), alpha‐linolenic and eicosapentaenoic were higher (p < 0.0001). Intra‐abdominal fat mass was higher (+25 %), however, the retroperitoneal adipocytes area was lower (?44 %). Femur mass (+10 %), distance between epiphyses (+4 %) and bone mineral density (+13 %) were higher. The study demonstrates that adequate flaxseed oil content during a lactation diet plays an important role in the development of pups.     

Filler Wetting in Miscible ESBR/SSBR Blends and Its Effect on Mechanical Properties

The selective wetting behavior of silica in emulsion styrene butadiene rubber (ESBR)/solution styrene butadiene rubber (SSBR) blends is characterized by the wetting concept, which is further developed for filled blends based on miscible rubbers. It is found that not only the chemical rubber–filler affinity but also the topology of the filler surface significantly influences the selective filler wetting in rubber blends. The nanopore structure of the silica surface has been recognized as the main reason for the difference in the wetting behavior of the branched ESBR molecules and linear SSBR molecules. However, the effect of nanopore structure becomes more significant in the presence of silane. It is discussed that the adsorption of silane on silica surface constricts the nanopore to some extent that hinders effectively the space filling of the nanopores by the branched ESBR molecules but not by the linear SSBR molecules. As a result, in silanized ESBR/SSBR blends the dominant wetting of silica surface by the tightly bonded layer of SSBR molecules causes a low‐energy dissipation in the rubber–filler interphase. That imparts the low rolling resistance to the blends similar to that of a silica‐filled SSBR compound, while the ESBR‐rich matrix warrants the good tensile behavior, i.e., good abrasion and wear resistance of the blends.